Detection of the presence of a human in an image is often useful, for example in surveillance applications, robotic applications, or as a preliminary operation in an image processing system. Unfortunately, automated human image detection is a relatively difficult computational problem due to the wide variations that are possible between images of different people. These variations may be related to general physical appearance, clothing, position and pose, illumination, and viewing angle, to name a few. Existing methods for human detection are typically limited to certain situations or scenarios that include, for example, a particular viewing angle, or the requirement that the person be in a specific pose with respect to the camera. These methods also tend to be computationally expensive, requiring large training databases and relatively fast processors. Even so, these methods tend not to be robust, resulting in unacceptable rates of false alarm and missed detections.
Although the following Detailed Description will proceed with reference being made to illustrative embodiments, many alternatives, modifications, and variations thereof will be apparent in light of this disclosure.